I am interested in exploring whether AI techniques can derive hidden patterns of relationships in a data set. For example, from among house size, lot size, age of house and asking price, what formula best predicts selling price?
In explorations around how this might be done, I tried to use a neural network to solve for a predictable relationship between two variables to predict a third, so I trained my neural network with inputs consisting of the length of two sides of a triangle, and the result being the length of the hypotenuse. It couldn't get it to work.
I was told by somebody who understands all this better than me that the reason it failed is because conventional neural networks are not good at modeling non-linear relationships.
If that is true, I wonder if there is some other AI technique that could 'derive' a network modeling the phythagorean theorem from a training data set with better results than a normal neural network?